IEEE Sensors Journal最新文献

{"title":"Highly Sensitive Gas Sensors Based on Sulfonated Peryleneimide Derivatives for NH3 Detection","authors":"Xiaoyun Chen;Jiaxing Wang;Wenjie Tao;Haotian Guo;Wenji Li;Zhankui Zhang;Xiaotian Liu;Xiaoguang Qiao","doi":"10.1109/JSEN.2026.3735308","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3735308","url":null,"abstract":"Ammonia sensors with high sensitivity, low detection limit, rapid response/recovery, and long-term stability are highly desirable. In order to acquire ammonia sensors with high sensitivity and low detection limit, a highly efficient chemiresistive sensor based on sulfonic acid group-functionalized perylenediimide derivatives (PDIs) (PC) was synthesized. In this design, we obtained three different morphologies of nanostructures by regulating the pH value of the PC self-assembly solution. The S=O groups on the side chain, as well as the C=O and C-N groups on the backbone, could absorb or release hydrogen ions in different pH environments, thereby influencing the hydrophilicity/hydrophobicity, <inline-formula> <tex-math>$pi $ </tex-math></inline-formula>–<inline-formula> <tex-math>$pi $ </tex-math></inline-formula> interaction, etc., ultimately affecting the sensing performance of ammonia. As a result, the deprotonation process of S=O, C=O, and C-N groups can weaken the formation of hydrogen bond interactions between molecules, promote the formation of <inline-formula> <tex-math>$pi $ </tex-math></inline-formula>–<inline-formula> <tex-math>$pi $ </tex-math></inline-formula> stacking and effective <inline-formula> <tex-math>$pi $ </tex-math></inline-formula>–<inline-formula> <tex-math>$pi $ </tex-math></inline-formula> overlap. The optimized sensor exhibits a large response of 600% to 20 ppm ammonia at room temperature, a rapid response/recovery time of 17.32/13.08 s, and a lower detection limit of 0.01 ppm. It has a promising application prospect in the freshness testing of shrimp.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"32123-32129"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EIT Imaging Method Based on B-Spline Feature Extraction and Sparse Reconstruction","authors":"Guoxing Huang;Xiaoming Fan;Xiangyi Bai;Jingwen Wang;Weidang Lu;Xiaoming Yin","doi":"10.1109/JSEN.2026.3733786","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3733786","url":null,"abstract":"Electrical Impedance Tomography (EIT) offers several advantages, including high temporal resolution, radiation-free operation, and low cost. However, its inverse problem is severely ill-posed, leading to low imaging accuracy and strong artifacts. These drawbacks limit its practical applications. To address this issue, this article proposes a novel EIT image reconstruction method based on B-spline feature extraction and sparse reconstruction. First, effective features from the conductivity distribution are extracted by B-spline kernels. Observation data are augmented by this process, and the ill-posedness of the inverse problem is mitigated accordingly. Subsequently, an enhanced composite observation model is constructed, and the image reconstruction task is transformed into an L0-norm optimization problem. This problem is solved by the adaptive spatial constrained orthogonal matching pursuit (ASCOMP) algorithm. ASCOMP can automatically determine the number of iterations, enhance spatial continuity, and produce globally optimal coefficients within each selected support set using a convex optimization subproblem. Finally, experimental validation was conducted using a 16-electrode hardware system. In simulations of six typical flow patterns, the new method achieved a correlation coefficient (CC) as high as 0.9272 and a relative error (RE) as low as 0.2839, with average values of 0.8933 and 0.3752, respectively, outperforming all other algorithms. Hardware experiments also demonstrated that it effectively suppresses artifacts and preserves target boundaries, performing particularly well in complex multitarget scenarios. In summary, this method provides an effective solution to the EIT inverse problem.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"33421-33433"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bridging Sensing and Memory With MXene Gasistors for Intelligent Artificial Olfaction: A Review","authors":"Hao Wang;Mei Ma;Yongchun Li;Hong Wang;Lijuan Qiao;Ge Li;Denglong Lu;Bingxin Liu","doi":"10.1109/JSEN.2026.3733316","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3733316","url":null,"abstract":"The rapid development of the Industrial Internet of Things (IIoT) and edge artificial intelligence has driven a paradigm shift from passive data acquisition toward active in situ processing. Although several reviews have addressed MXene-based chemiresistors and standalone memristors, a dedicated review of gasistors, which integrate sensing and memristive coupling within a single device, remains lacking. This review first systematically examines the device architectures of MXene-based gasistors and then elaborates on how the metallic conductivity and chemically tunable surface terminations of MXenes enable simultaneous rapid charge readout and programmable resistive switching. In particular, it highlights that gas adsorption can directly modulate conductive filament (CF) dynamics and Schottky barrier height, thereby distinguishing intrinsically coupled gasistors from series-assembled sensor-memristor devices. Moreover, the capability of these devices to emulate synaptic plasticity is discussed in the context of millisecond-scale neuromorphic olfactory applications. Finally, the review evaluates the key bottlenecks toward practical deployment, including oxidation stability and wafer-scale uniformity, and outlines future directions for constructing stable and practical cognitive sensing systems.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"31984-32009"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inertial Sensing-Based Adaptive Neural Network for Lower Limb Joint Angle Prediction in Continual Multiscenario Assistive Locomotion","authors":"Shengzheng Kang;Shengli Mao;Yao Li;Wenjie Pan;Peng Zhang;Peiang Yang;Xiaolong Yang","doi":"10.1109/JSEN.2026.3733695","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3733695","url":null,"abstract":"Accurate joint angle prediction is crucial for achieving efficient assistive control in lower limb exoskeletons. However, accurate prediction remains challenging because of user variability, different locomotion terrains, and sudden gait changes. This article proposes a novel lower limb joint angle prediction model (ARBFNN-EPD) that integrates an adaptive radial basis function neural network with enhanced proportional-derivative (EPD) feedback adjustment. In this means, the proposed model enables high prediction accuracy even though exoskeletons suffer from user variability, different terrains, and sudden gait changes. To construct a representative training dataset, continuous multiscenario locomotion data are collected from ten human subjects, each leg equipped with three inertial measurement units (IMUs). Based on the collected datasets, the proposed model is cross-validated offline, and the prediction results of three joint angles (i.e., hip, knee, and ankle) for the time horizon of 150 ms demonstrate that, the ARBFNN-EPD can achieve the smallest root-mean-square error (RMSE) of <inline-formula> <tex-math>$5.26^{circ } ~pm ~1.17^{circ } $ </tex-math></inline-formula>, mean absolute error (MAE) of <inline-formula> <tex-math>$4.38^{circ } ~pm ~1.05^{circ } $ </tex-math></inline-formula>, and R-square (R²) of <inline-formula> <tex-math>$0.95~pm ~0.02$ </tex-math></inline-formula>, respectively, compared with four other neural network-based methods such as the backpropagation neural network (BPNN), radial basis function neural network (RBFNN), long short-term memory network (LSTM), and locomotion mode prior-based (LM-Prior) model. Finally, the model is deployed in a real-world lower limb exoskeleton, and the cross-subject tests show that the ARBFNN-EPD provides the RMSE of <inline-formula> <tex-math>$5.92^{circ } ~pm ~1.97^{circ } $ </tex-math></inline-formula>, MAE of <inline-formula> <tex-math>$4.51^{circ } ~pm ~1.42^{circ } $ </tex-math></inline-formula>, and R² of <inline-formula> <tex-math>$0.93~pm ~0.03$ </tex-math></inline-formula> at 150 ms, where the MAE outperforms the BPNN (78.61%), RBFNN (58.47%), LSTM (34.54%), and LM-Prior (10.69%), further proving the superior performance of the proposed model on the online joint angle prediction capability.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"32959-32969"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Imperfect Spectrum Sensing-Based Interring Energy Balance-Oriented Multihop Uneven Clustering Routing Protocol for Active IRS-Assisted CRSNs","authors":"Jihong Wang;Liubo Dong;Xitong Su;Miao Yu;Yang Li","doi":"10.1109/JSEN.2026.3733071","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3733071","url":null,"abstract":"Conventional uneven clustering routing protocols for cognitive radio sensor networks (CRSNs) often rely on direct node-to-sink transmission and assume perfect spectrum sensing, thereby significantly limiting network lifetime. Motivated by these critical limitations, this article introduces active intelligent reflecting surface (IRS) technology and proposes an imperfect spectrum sensing-based interring energy balance-oriented multihop uneven clustering routing protocol (IPSS-IEBMUCRP) tailored for active IRS-assisted CRSNs. In particular, according to key sensing parameters, such as noise variance, received signal power from primary users (PUs), number of sampling observations, and channel occupancy probabilities, three strategies are introduced to determine the optimal energy detection threshold and facilitate reliable spectrum sensing in CRSNs. By embedding a normalized detection accuracy function into both cluster formation and multihop routing selection, IPSS-IEBMUCRP prioritizes nodes with superior sensing accuracy and richer channel availability to act as cluster heads (CHs) and relays, thereby strengthening the network’s spectrum awareness and monitoring capabilities. Simulation results indicate that IPSS-IEBMUCRP significantly outperforms baseline protocols, improving the packet delivery ratio by up to 74% and extending network lifetime by up to 194%.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"33380-33391"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Geometry-Driven 3-D Point Cloud Sensor System for Tire Tread Defect Detection","authors":"Yifei You;Tong Zhang;Wenhua Jiao;Yongtong Pan;Guolong Deng;Zhenwen Liu","doi":"10.1109/JSEN.2026.3731852","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3731852","url":null,"abstract":"Automated inspection of tire tread geometry is complicated by localized manufacturing deviations, repetitive tread patterns, and deep circumferential grooves. In reference-based point-cloud inspection, these structures can create ambiguous alignments and spatially varying residual baselines, so a large residual does not necessarily identify the defective tread block. We present TireCurv-Inspect, a geometry-driven framework for 3-D tire tread inspection. The framework treats defects as localized deviations from a defect-free reference and links four operations: curvature-guided registration initialization, structure-aware alignment refinement, groove-based tread partitioning, and robust within-window residual normalization. This design addresses a specific failure mode of direct geometric comparison: a low registration residual can still arise from an incorrect correspondence between repetitive tread elements. The framework was evaluated on industrial point clouds spanning five tread patterns. Relative to the evaluated registration baselines, it reduced the root-mean-square error (RMSE) to 0.319 mm and placed the annotated defective block first in 82.4% of 204 defective windows and within the top two in 96.1%. These results support interpretable block-level localization under the evaluated reference-based setting. The current evidence does not establish reference-free operation or production-line throughput.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"33292-33304"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensor Response-Time Reduction Using Long Short-Term Memory Network Forecasting","authors":"Simon J. Ward;Muhamed Baljevic;Sharon M. Weiss","doi":"10.1109/JSEN.2026.3724771","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3724771","url":null,"abstract":"The response time of a biosensor is a crucial metric in safety-critical applications such as medical diagnostics where an earlier diagnosis can markedly improve patient outcomes. However, the speed at which a biosensor reaches a final equilibrium state can be limited by poor mass transport and long molecular diffusion timescales that increase the time it takes target molecules to reach the active sensing region. While system and sensor design optimization can promote molecules reaching the sensing element faster, a simpler and complementary approach for response-time reduction that is widely applicable across many sensor platforms is using time-series forecasting to predict the steady-state sensor response. Here, we show that ensembles of long short-term memory (LSTM) networks can accurately predict equilibrium biosensor response from limited initial time-dependent biosensor measurements, reducing response time by a mean and median factor of improvement of 18.6 and 5.1, respectively. The ensemble of models also provides simultaneous uncertainty estimation, essential for confident predictions and subsequent safety-related decisions. This approach is demonstrated on real-time experimental data collected by exposing porous silicon (PSi) biosensors to buffered protein solutions using a multichannel fluidic cell, automating the measurement of 100 biosensors in parallel. The dramatic improvement in response time achieved using LSTM network ensembles and associated uncertainty quantification opens the door to trustworthy and faster-responding biosensors, enabling more rapid medical diagnostics for faster clinical decision making that can lead to improved patient outcomes and healthcare access, as well as quicker identification of toxins in food and the environment.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"32616-32629"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11664256","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Catalyst-Dependent Solar-Blind Photodetection in β-Ga2O3 Nanowire Network MSM Photodetectors","authors":"Jung-Bok Lee;Jiheon Ha;Nakhee Kang;Bumhwan Kim;Dongho Lee;Bombi Kim;Minseok Jang;Ogyun Seok;Ho-Jun Lee","doi":"10.1109/JSEN.2026.3733395","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3733395","url":null,"abstract":"Solar-blind ultraviolet (UV) photodetectors based on <inline-formula> <tex-math>$beta $ </tex-math></inline-formula>-Ga₂O₃ have attracted significant attention owing to their ultrawide bandgap and intrinsic visible-blind characteristics. In this work, catalyst-assisted <inline-formula> <tex-math>$beta $ </tex-math></inline-formula>-Ga₂O₃ nanowire (NW) networks were directly grown on c-plane sapphire substrates by pulsed laser deposition (PLD) using ultrathin metal catalyst layers (Au, Ag, Cu, Ni, and Ti), followed by the fabrication of Ti/Au-contacted metal–semiconductor–metal (MSM) photodetectors. By systematically varying only the catalyst species under otherwise identical growth and device conditions, the effects of catalyst selection on NW morphology and photodetector performance were directly compared. The catalyst species strongly influenced both the morphology of the as-grown NWs and the electrical/photoresponse characteristics of the resulting devices. Under 254-nm illumination, the Ag-assisted device exhibited the highest photocurrent-related performance, including the highest responsivity, external quantum efficiency (EQE), and specific detectivity (D<inline-formula> <tex-math>${}^{ast } $ </tex-math></inline-formula>). On the contrary, the Ni-assisted device showed the lowest dark current and the highest photo-to-dark current ratio (PDCR), indicating a clear catalyst-dependent tradeoff between high-responsivity operation and low-leakage, high-contrast photodetection. The observed catalyst-dependent trends are likely associated with the coupled effects of NW morphology, network connectivity, and defect-related carrier transport, rather than a single growth-related factor alone. These results suggest that catalyst engineering is an effective process-level strategy for tailoring <inline-formula> <tex-math>$beta $ </tex-math></inline-formula>-Ga₂O₃ NW network MSM photodetectors for either high-responsivity or low-leakage, high-contrast UV photodetection.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"32325-32332"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Lightweight Scale-Adaptive Detector for Small UAV Detection in Complex Scenarios","authors":"Bingling Tang;Chi Wang","doi":"10.1109/JSEN.2026.3735359","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3735359","url":null,"abstract":"Distant uncrewed aerial vehicles (UAVs) usu-ally appear with small object sizes, weak textures, blurry boundaries, and severe background interference, which poses significant challenges for object detection in anti-UAV scenarios. Existing efficient detectors still suffer from feature degradation during repeated downsampling, and fixed receptive-field feature fusion is insufficient to handle the large scale variations caused by different target distances. To address these problems, this article proposes a lightweight scale-adaptive detector for anti-UAV small-object detection. Specifically, a Micro-target Contrast Enhancement (MCE) module is designed to reorganize shallow features by jointly modeling original appearance information, local contrast residuals, and surrounding contextual cues, thereby strengthening weak UAV responses in shallow high-resolution features. A Scale-adaptive Multireceptive-field Feature Fusion (SMFF) module is further proposed to perform location-dependent fusion among complementary local and contextual sampling patterns through branch-wise normalized weights, improving the adaptability of the detector to UAVs at different scales. Moreover, a detail-preserving adaptive downsampling (DPAD) module is developed to reduce small-object information loss during downsampling by adaptively integrating a detail branch and an anti-aliasing branch. By jointly organizing shallow local-contrast and contextual cues, adaptively allocating complementary local and contextual observations, and preserving fine-grained details during feature propagation, the proposed detector better handles distant UAV detection in complex backgrounds. Experiments on the Dalian University of Technology (DUT)-Anti-UAV and Anti-UAV (Inf) datasets demonstrate that the proposed method improves detection accuracy and small-object performance while maintaining a lightweight model structure and competitive computational cost.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"33144-33160"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fringe Projection 3-D Imaging Based on Frequency Presimulation Optimization","authors":"Jianhua Wang;Huixin Sun;Qinkui Ma;Tong Shao","doi":"10.1109/JSEN.2026.3733633","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3733633","url":null,"abstract":"In fringe projection 3-D imaging, sensor errors, quantization errors, and ambient light inevitably introduce random noise, further leading to absolute phase recovery (APR) errors. Different frequency allocation in the three-frequency temporal phase unwrapping (TPU) has a significant impact on the antinoise performance. However, there is currently no optimal frequency allocation method for three-frequency TPU. In this article, we first propose an optimal fringe period design method based on numerical simulation. We analyze the main factor that affects the accuracy of three-frequency phase unwrapping in fringe projection profilometry (FPP), establish the absolute phase error model, use numerical simulation to determine the optimal mid-frequency fringe period range for three-frequency TPU, and discuss the influence of fringe period selection on APR accuracy. The experimental comparison proves that selecting the recommended mid- frequency fringe period can effectively reduce the noise-induced absolute phase error.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 21","pages":"32917-32928"},"PeriodicalIF":4.5,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149315619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}